


***/// NOTE: This code reproduces the findings in Pickett et al. (2024) "Officer Diversity Reduces Black Americans’ Fear of the Police" ///***

***/// COMMANDS NEEDED: coefplot, norm, and vioplot; Analysis done in Stata 16 ///***



*************************//// Generate Measures ////*************************



***/// Dependent Variable - Personal Fear of Police ///***


recode Q1_1 (5=0) (4=1) (3=2) (2=3) (1=4), gen(stopyou)
recode Q1_2 (5=0) (4=1) (3=2) (2=3) (1=4), gen(searchyou)
recode Q1_3 (5=0) (4=1) (3=2) (2=3) (1=4), gen(yellyou)
recode Q1_4 (5=0) (4=1) (3=2) (2=3) (1=4), gen(handcyou)
recode Q1_5 (5=0) (4=1) (3=2) (2=3) (1=4), gen(kickyou)
recode Q1_6 (5=0) (4=1) (3=2) (2=3) (1=4), gen(pinyou)
recode Q1_7 (5=0) (4=1) (3=2) (2=3) (1=4), gen(sprayyou)
recode Q1_8 (5=0) (4=1) (3=2) (2=3) (1=4), gen(taseyou)
recode Q1_9 (5=0) (4=1) (3=2) (2=3) (1=4), gen(shootyou)
recode Q1_10 (5=0) (4=1) (3=2) (2=3) (1=4), gen(killyou)
label define fear 0 "0. Very Unafraid" 1 "1. Unafraid" 2 "2. Neither" 3 "3. Afraid" 4 "4. Very Afraid"
label values stopyou searchyou yellyou handcyou kickyou pinyou sprayyou taseyou shootyou killyou fear
factor stopyou searchyou yellyou handcyou kickyou pinyou sprayyou taseyou shootyou killyou, mine(1)
alpha stopyou searchyou yellyou handcyou kickyou pinyou sprayyou taseyou shootyou killyou
egen pfear = rmean(stopyou searchyou yellyou handcyou kickyou pinyou sprayyou taseyou shootyou killyou)
label variable pfear "Index: Personal Fear of Police"

norm pfear, method(mmx)
gen normpf = mmx_pfear*100
label variable normpf "Normalized: Personal Fear"


***/// Dependent Variable - Personal Fear of Crime ///***


recode Q16_1 (5=0) (4=1) (3=2) (2=3) (1=4), gen(steal)
recode Q16_2 (5=0) (4=1) (3=2) (2=3) (1=4), gen(break)
recode Q16_3 (5=0) (4=1) (3=2) (2=3) (1=4), gen(rob)
recode Q16_4 (5=0) (4=1) (3=2) (2=3) (1=4), gen(rape)
recode Q16_5 (5=0) (4=1) (3=2) (2=3) (1=4), gen(murder)
label values steal break rob rape murder fear
factor steal break rob rape murder, mine(1)
alpha steal break rob rape murder
egen cfear = rmean(steal break rob rape murder)
label variable cfear "Index: Fear of Crime"


***/// Dependent Variable - Relative Fear of Police vs. Crime ///***


gen relfear = pfear - cfear
label variable relfear "Relative Fear: Police to Crime"
recode relfear (-4/-.00001 = 0) (0 = 1) (.00001/4 = 2), gen (relfearc)
label define relfearc 0 "0. More Afraid of Crime" 1 "1. Equally Afraid" 2 "2. More Afraid of Police"
label values relfearc relfearc


***/// Dependent Variable - Specific Fear of Pictured Police ///***


recode Q7_1 (5=0) (4=1) (3=2) (2=3) (1=4), gen(hurtyou)
recode Q7_2 (5=0) (4=1) (3=2) (2=3) (1=4), gen(useforce)
recode Q7_3 (5=0) (4=1) (3=2) (2=3) (1=4), gen(weapon)
recode Q7_4 (5=0) (4=1) (3=2) (2=3) (1=4), gen(warrest)
label values hurtyou useforce weapon warrest fear
factor hurtyou useforce weapon warrest, mine(1)
alpha hurtyou useforce weapon warrest
egen sfear = rmean(hurtyou useforce weapon warrest)
label variable sfear "Index: Specific Fear of Police"

norm sfear, method(mmx)
gen normsf = mmx_sfear*100
label variable normsf "Normalized: Specific Fear"


***/// Independent Variables - Group Composition of Pictured Officers ///***


gen offrace = .
replace offrace = 0 if po_race1 ==0 & po_race2 ==0
replace offrace = 1 if po_race1 > 0 
replace offrace = 1 if po_race2 > 0 
replace offrace = 2 if po_race1 >0 & po_race2 >0 
replace offrace = . if po_race1 ==.
replace offrace = . if po_race2 ==.
label define offrace 0 "Both White" 1 "Mixed" 2 "Both Minorities"
label values offrace offrace

gen offsex = .
replace offsex = 0 if po_sex1 ==0 & po_sex2 ==0
replace offsex = 1 if po_sex1 ==1 
replace offsex = 1 if po_sex2 ==1
replace offsex = 2 if po_sex1 ==1 & po_sex2 ==1
label define offsex 0 "Both Male" 1 "Mixed" 2 "Both Female" 
label values offsex offsex


***/// Independent Variable - Respondent Race ///***


recode race (1=0) (2=2) (3/8=1), gen (raceg)
label define raceg 0 "0. White" 1 "1. Other" 2 "2. Black"
label values raceg raceg
label variable raceg "Respondent Race"

recode raceg (0=0) (2=1) (else = .), gen (blackwhite)
label define blackwhite 0 "0. White" 1 "1. Black"
label values blackwhite blackwhite
label variable blackwhite "Compare by Race"

clonevar otherblack = raceg 
recode otherblack (0=.) (1=0) (2=1)
label define otherblack 0 "0. Other Minority" 1 "1. Black"
label values otherblack otherblack
label variable otherblack "Compare Minorities"


***/// Control Variable - Experiences With Police Mistreatment ///***


gen stopped = Q18_1 - 1
gen insulted = Q18_2 - 1
gen abused = Q18_3 - 1

factor stopped insulted abused
alpha stopped insulted abused, gen (mistreat)
label variable mistreat "Index: Past Mistreatment"
pwcorr pfear mistreat, sig



*************************//// Appendix: Sample Descriptive Statistics ////*************************



***/// Generate Variables ///***


gen age = 2022 - birthyr
label variable age "Respondent Age in Years"

recode gender (2=1) (1=0), gen (female)
label define female 0 "0. Male" 1 "1. Female"
label values female female
label variable female "Respondent Gender"

gen education = educ - 1
label define education 0 "0.  No HS" 1 "1. High school" 2 "2. Some college" 3 "3. 2-year" 4 "4. 4-year" 5 "5. Post-grad"
label values education education
label variable education "Respondent Education"

clonevar income = faminc_new
recode income (97 =.)
replace income = income - 1
label define income 0 "0. Less than $10,000" 1 "1. $10,000 - $19,999" 2 "2. $20,000 - $29,999" 3 "3. $30,000 - $39,999" 4 "4. $40,000 - $49,999" 5 "5. $50,000 - $59,999" 6 "6. $60,000 - $69,999" 7 "7. $70,000 - $79,999" 8 "8. $80,000 - $99,999" 9 "9. $100,000 - $119,999" 10 "10. $120,000 - $149,999" 11 "11. $150,000 - $199,999" 12 "12. $200,000 - $249,999" 13 "13. $250,000 - $349,999" 14 "14. $350,000 - $499,999"  15 "15.$500,000 or more"      
label values income income
label variable income "Family Income"

recode employ (3 4 =1) (.=.) (else =0), gen (unemploy)
label variable unemploy "Respondent Employment Status"
label define unemploy 0 "0. Other" 1 "1. Unemployed or Laid Off"
label values unemploy unemploy

clonevar married = marstat
recode married (2/6 =0) 
label variable married "Respondent Marital Status"

clonevar hchild = child18
recode hchild (2=0)
label variable hchild "Household Child <18"

gen party = pid7 - 1
replace party = 3 if pid7 == 8 & pid3 == 3
recode party (7=.)
label define party 0 "0. Strong Democrat" 1 "1. Not very strong Democrat" 2 "2. Lean Democrat" 3 "3. Independent" 4 "4. Lean Republican" 5 "5. Not very strong Republican" 6 "6. Strong Republican" 
label values party party
label variable party "Party Identification"

gen ideology = ideo5 - 1
recode ideology (5=.) 
label define ideology 0 "0. Very Liberal" 1 "1. Liberal" 2 "2. Moderate" 3 "3. Conservative" 4 "4. Very Conservative" 
label values ideology ideology 
label variable ideology "Political Ideology"

gen usr = 5 - urbanicity2 
label define usr 0 "0. Rural Area" 1 "1. Small Town" 2 "2. Suburban Area" 3 "3. Smaller city" 4 "4. Big City"
label values usr usr
label variable usr "Urbanicity"

recode inputstate (9 23 25 33 44 50 34 36 42 =0) (17 18 26 39 55 19 20 27 29 31 38 46 =1) ///
	(10 11 12 13 24 37 45 51 54 1 21 28 47 5 22 40 48 =2) (4 8 16 30 32 35 49 56 2 6 15 41 53 = 3), gen (region)
label define region 0 "0. Northeast" 1 "1. Midwest" 2 "2. South" 3 "3. West"
label values region region
label variable region "Region of Residence"

tab education, gen (educ)
tab raceg, gen(raceg)
tab party, gen(party)
tab ideology, gen(ideology)
tab usr, gen (usr)
tab region, gen(region)


***/// General Population Sample Descriptives ///***


svyset [pw = weight_gp]
svy: mean raceg1 raceg2 raceg3 
estat sd
svy: mean female
estat sd
svy: mean age 
estat sd 
svy: mean educ1 educ2 educ3 educ4 educ5 educ6 
estat sd
svy: mean income
estat sd
svy: mean unemploy
estat sd
svy: mean married 
estat sd 
svy: mean hchild 
estat sd
svy: mean party1 party2 party3 party4 party5 party6 party7 
estat sd 
svy: mean ideology1 ideology2 ideology3 ideology4 ideology5 
estat sd 
svy: mean usr1 usr2 usr3 usr4 usr5 
estat sd
svy: mean region1 region2 region3 region4 
estat sd


***/// General Population Comparison to US Population ///***


svy: proportion race

recode age (19/44 = 0) (45/95 = 1), gen (older45)
label define older45 0 "0. Under 45" 1 "1. 45 or older"
label values older45 older45
svy: proportion older45

recode age (19/64 = 0) (65/95 = 1), gen (older65)
label define older65 0 "0. Under 65" 1 "1. 65 or older"
label values older65 older65
svy: proportion older65

recode education (0/3 = 0) (4 5 = 1), gen (bdegree)
label define bdegree 0 "0. Less than BA" 1 "1. BA degree or higher"
label values bdegree bdegree 
svy: proportion bdegree

recode race (1=1) (2/8 =0), gen (wfemale)
replace wfemale = 0 if female ==0
label define wfemale 0 "0. Other" 1 "1.White woman"
label values wfemale wfemale
svy: proportion wfemale

clonevar female65 = female
replace female65 = 0 if older65 ==0
label define female65 0 "0. Other" 1 "1. Woman over 65"
label values female65 female65
svy: proportion female65

clonevar degree65 = older65
replace degree65 = 0 if bdegree ==0
label define degree65 0 "0. Other" 1 "1. BA degree, 65+"
label values degree65 degree65 
svy: proportion degree65

recode party (0 1 =0) (2 3 4 =1) (5 6 =2), gen (partyc)
label define partyc 0 "0. Democrat" 1 "1. Independent" 2 "2. Republican"
label values partyc partyc
svy: proportion partyc

recode presvote20post (2=1) (6=.) (1 3 4 5 =0), gen (voteTrump20)
label define voteTrump20 0 "0. Voted for Other" 1 "1. Voted for Trump"
label values voteTrump20 voteTrump20
replace voteTrump20 = . if votereg ==2
replace voteTrump20 = . if votereg ==3
svy: proportion voteTrump20
svyset, clear


***/// Black Oversample Descriptives ///***


svyset [pw = weight_aa]
svy: mean female if weight_gp ==.
estat sd
svy: mean age if weight_gp ==.
estat sd 
svy: mean educ1 educ2 educ3 educ4 educ5 educ6 if weight_gp ==.
estat sd
svy: mean income if weight_gp ==.
estat sd
svy: mean unemploy if weight_gp ==.
estat sd
svy: mean married if weight_gp ==.
estat sd 
svy: mean hchild if weight_gp ==.
estat sd
svy: mean party1 party2 party3 party4 party5 party6 party7 if weight_gp ==.
estat sd 
svy: mean ideology1 ideology2 ideology3 ideology4 ideology5 if weight_gp ==.
estat sd 
svy: mean usr1 usr2 usr3 usr4 usr5 if weight_gp ==.
estat sd
svy: mean region1 region2 region3 region4 if weight_gp ==.
estat sd


***/// Black Oversample Comparison to US Black Population (NOTE: for education, Limited to 25+ to match Census Table) ///***


svy: proportion older45 if weight_gp ==.
svy: proportion older65 if weight_gp ==.
svy: proportion bdegree if age >24 & weight_gp ==.

recode party (0 1 2 =0) (3=1) (4 5 6 =2), gen (partylean)
label define partylean 0 "0. Democrat or Lean" 1 "1. Independent" 2 "2. Republican or Lean"
label values partylean partylean
svy: proportion partylean if weight_gp ==.
svy: proportion voteTrump20 if weight_gp ==.
svyset, clear



*************************//// Weighting for Main Analysis ////*************************



gen combweight = weight_aa
replace combweight = weight_gp if combweight ==.
label variable combweight "Combined Weight for Full Sample"
svyset [pw = combweight]



*************************//// Main Analysis, Other Than Conjoint ////*************************



***/// General Fear of the Police and Crime, By Race ///***


recode killyou (0 1 =0) (2=1) (3 4 =2), gen (killyoub)
label define catfear 0 "0. Unafraid" 1 "1. Neither" 2 "2. Afraid"
label values killyoub catfear
svy: proportion killyoub if blackwhite ==1
svy: proportion killyoub if blackwhite ==0
svy: proportion killyoub if raceg ==1

ttest pfear, by (blackwhite)
svy: mean pfear if blackwhite ==0
estat sd
svy: mean pfear if blackwhite ==1
estat sd
svy: regress pfear i.blackwhite

svy: regress rape i.female

ttest pfear, by (otherblack)
svy: mean pfear if otherblack ==0
estat sd
svy: mean pfear if otherblack ==1
estat sd
svy: regress pfear i.otherblack

ttest cfear, by (blackwhite)
svy: mean cfear if blackwhite ==0
estat sd
svy: mean cfear if blackwhite ==1
estat sd
svy: regress cfear i.blackwhite

ttest cfear, by (otherblack)
svy: mean cfear if otherblack ==0
estat sd
svy: mean cfear if otherblack ==1
estat sd
svy: regress cfear i.otherblack

svy: proportion relfearc if blackwhite ==1
svy: proportion relfearc if blackwhite ==0
svy: proportion relfearc if raceg ==1

ttest relfear, by (blackwhite)
svy: mean relfear if blackwhite ==0
estat sd
svy: mean relfear if blackwhite ==1
estat sd
svy: regress relfear i.blackwhite

ttest relfear, by (otherblack)
svy: mean relfear if otherblack ==0
estat sd
svy: mean relfear if otherblack ==1
estat sd
svy: regress relfear i.otherblack


***/// Figure 2: General Fear of the Police and Crime, By Race ///***


twoway kdensity pfear if blackwhite ==0 [aw = combweight], recast(area) color(%50) || kdensity pfear ///
	if blackwhite ==1 [aw = combweight], recast(area) color(%50) || kdensity pfear if raceg ==1 [aw = combweight]
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit yaxis1.title.text = {}
gr_edit yaxis1.title.text.Arrpush Density
gr_edit xaxis1.title.text = {}
gr_edit xaxis1.title.text.Arrpush Index: Personal Fear of the Police 
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush White
gr_edit legend.plotregion1.label[2].text = {}
gr_edit legend.plotregion1.label[2].text.Arrpush Black
gr_edit legend.plotregion1.label[3].text = {}
gr_edit legend.plotregion1.label[3].text.Arrpush Other Race
gr_edit legend.Edit , style(col_gap(small)) style(key_gap(minuscule)) style(key_xsize(medium)) keepstyles 
gr_edit xaxis1.title.style.editstyle margin(medsmall) editcopy
gr_edit plotregion1.plot1.style.editstyle area(shadestyle(intensity(50))) editcopy
gr_edit yaxis1.reset_rule 0 .4 .1 , tickset(major) ruletype(range)
gr_edit legend.draw_view.setstyle, style(no)

proportion killyou if blackwhite ==0 [pw = combweight]
estimates store whitekillyou
proportion killyou if blackwhite ==1 [pw = combweight]
estimates store blackkillyou
proportion killyou if raceg ==1 [pw = combweight]
estimates store otherkillyou

coefplot (whitekillyou, offset(-.15)recast(bar) barwidth(0.3) fcolor(*.5)) (blackkillyou, ///
	offset(.15)recast(bar) barwidth(0.3) fcolor(*.5)) (otherkillyou, offset(0)recast(line) lwidth(*2) ///
	ciopts(recast(rline) lp(dash))), ciopts(recast(rcap))citop citype(logit) legend(rows(1)) ///
	xtitle(Fear of Being Killed by the Police) ytitle(Proportion) vertical
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 1 1 `"VU"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 2 2 `"U"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 3 3 `"N"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 4 4 `"A"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 5 5 `"VA"', tickset(major)
gr_edit xaxis1.title.style.editstyle margin(medsmall) editcopy
gr_edit yaxis1.reset_rule 0 .5 .1 , tickset(major) ruletype(range) 
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomin(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_min(yes))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomax(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_max(yes))) editcopy
gr_edit legend.plotregion1.key[2].view.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit legend.plotregion1.key[2].view.style.editstyle area(linestyle(width(medium))) editcopy
gr_edit legend.plotregion1.key[1].view.style.editstyle area(shadestyle(intensity(50))) editcopy
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush White
gr_edit legend.plotregion1.label[2].text = {}
gr_edit legend.plotregion1.label[2].text.Arrpush Black
gr_edit legend.plotregion1.label[3].text = {}
gr_edit legend.plotregion1.label[3].text.Arrpush Other Race
gr_edit legend.plotregion1.key[1].xsz.editstyle 6 editcopy
gr_edit legend.plotregion1.key[2].xsz.editstyle 6 editcopy
gr_edit legend.Edit , style(col_gap(small)) style(key_gap(minuscule)) style(key_xsize(medium)) keepstyles 
gr_edit legend.draw_view.setstyle, style(no)

twoway kdensity cfear if blackwhite ==0 [aw = combweight], recast(area) color(%50) || kdensity cfear ///
	if blackwhite ==1 [aw = combweight], recast(area) color(%50) || kdensity cfear if raceg ==1 [aw = combweight]
gr_edit yaxis1.reset_rule 0 .4 .1 , tickset(major) ruletype(range) 
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomin(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_min(yes))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomax(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_max(yes))) editcopy
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit yaxis1.title.text = {}
gr_edit yaxis1.title.text.Arrpush Density
gr_edit xaxis1.title.text = {}
gr_edit xaxis1.title.text.Arrpush Index: Personal Fear of Crime 
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush White
gr_edit legend.plotregion1.label[2].text = {}
gr_edit legend.plotregion1.label[2].text.Arrpush Black
gr_edit legend.plotregion1.label[3].text = {}
gr_edit legend.plotregion1.label[3].text.Arrpush Other Race
gr_edit legend.Edit , style(col_gap(small)) style(key_gap(minuscule)) style(key_xsize(medium)) keepstyles 
gr_edit xaxis1.title.style.editstyle margin(medsmall) editcopy
gr_edit plotregion1.plot1.style.editstyle area(shadestyle(intensity(50))) editcopy
gr_edit legend.draw_view.setstyle, style(no)

proportion murder if blackwhite ==0 [pw = combweight]
estimates store whitemur
proportion murder if blackwhite ==1 [pw = combweight]
estimates store blackmur
proportion murder if raceg ==1 [pw = combweight]
estimates store othermur

coefplot (whitemur, offset(-.15)recast(bar) barwidth(0.3) fcolor(*.5)) (blackmur, ///
	offset(.15)recast(bar) barwidth(0.3) fcolor(*.5)) (othermur, offset(0)recast(line) lwidth(*2) ///
	ciopts(recast(rline) lp(dash))), ciopts(recast(rcap))citop citype(logit) legend(rows(1)) ///
	xtitle(Fear of Being Murdered by Criminals) ytitle(Proportion) vertical
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 1 1 `"VU"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 2 2 `"U"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 3 3 `"N"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 4 4 `"A"', tickset(major)
gr_edit xaxis1.major.num_rule_ticks = 0
gr_edit xaxis1.edit_tick 5 5 `"VA"', tickset(major)
gr_edit xaxis1.title.style.editstyle margin(medsmall) editcopy
gr_edit yaxis1.reset_rule 0 .5 .1 , tickset(major) ruletype(range) 
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomin(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_min(yes))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomax(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_max(yes))) editcopy
gr_edit legend.plotregion1.key[2].view.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit legend.plotregion1.key[2].view.style.editstyle area(linestyle(width(medium))) editcopy
gr_edit legend.plotregion1.key[1].view.style.editstyle area(shadestyle(intensity(50))) editcopy
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush White
gr_edit legend.plotregion1.label[2].text = {}
gr_edit legend.plotregion1.label[2].text.Arrpush Black
gr_edit legend.plotregion1.label[3].text = {}
gr_edit legend.plotregion1.label[3].text.Arrpush Other Race
gr_edit legend.plotregion1.key[1].xsz.editstyle 6 editcopy
gr_edit legend.plotregion1.key[2].xsz.editstyle 6 editcopy
gr_edit legend.Edit , style(col_gap(small)) style(key_gap(minuscule)) style(key_xsize(medium)) keepstyles 
gr_edit legend.draw_view.setstyle, style(no)

twoway kdensity relfear if blackwhite ==0 [aw = combweight], recast(area) color(%50) || kdensity relfear ///
	if blackwhite ==1 [aw = combweight], recast(area) color(%50) || kdensity relfear if raceg ==1 [aw = combweight]
gr_edit yaxis1.reset_rule 0 .5 .1 , tickset(major) ruletype(range) 
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomin(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_min(yes))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomax(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_max(yes))) editcopy
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit yaxis1.title.text = {}
gr_edit yaxis1.title.text.Arrpush Density
gr_edit xaxis1.title.text = {}
gr_edit xaxis1.title.text.Arrpush Relative Personal Fear: Crime vs. Police
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush White
gr_edit legend.plotregion1.label[2].text = {}
gr_edit legend.plotregion1.label[2].text.Arrpush Black
gr_edit legend.plotregion1.label[3].text = {}
gr_edit legend.plotregion1.label[3].text.Arrpush Other Race
gr_edit legend.Edit , style(col_gap(small)) style(key_gap(minuscule)) style(key_xsize(medium)) keepstyles 
gr_edit xaxis1.title.style.editstyle margin(medsmall) editcopy
gr_edit plotregion1.plot1.style.editstyle area(shadestyle(intensity(50))) editcopy
gr_edit legend.draw_view.setstyle, style(no)

proportion relfearc if blackwhite ==0 [pw = combweight]
estimates store whiterf
proportion relfearc if blackwhite ==1 [pw = combweight]
estimates store blackrf
proportion relfearc if raceg ==1 [pw = combweight]
estimates store otherrf

coefplot (whiterf, offset(-.15)recast(bar) barwidth(0.3) fcolor(*.5)) (blackrf, offset(.15)recast(bar) barwidth(0.3) fcolor(*.5)) ///
	(otherrf, offset(0)recast(line) lwidth(*2) ciopts(recast(rline) lp(dash))), ciopts(recast(rcap))citop citype(logit) legend(rows(1)) ///
	xtitle(Relative Personal Fear: Categorical) ytitle(Proportion) vertical
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit xaxis1.edit_tick 1 1 `"Crime"', tickset(major)
gr_edit xaxis1.edit_tick 2 2 `"Equally Afraid"', tickset(major)
gr_edit xaxis1.edit_tick 3 3 `"Police"', tickset(major)
gr_edit xaxis1.title.style.editstyle margin(medsmall) editcopy
gr_edit yaxis1.reset_rule 0 .7 .1 , tickset(major) ruletype(range) 
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomin(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_min(yes))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(force_nomax(no))) editcopy
gr_edit yaxis1.style.editstyle majorstyle(gridstyle(draw_max(yes))) editcopy
gr_edit legend.plotregion1.key[2].view.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit legend.plotregion1.key[2].view.style.editstyle area(linestyle(width(medium))) editcopy
gr_edit legend.plotregion1.key[1].view.style.editstyle area(shadestyle(intensity(50))) editcopy
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush White
gr_edit legend.plotregion1.label[2].text = {}
gr_edit legend.plotregion1.label[2].text.Arrpush Black
gr_edit legend.plotregion1.label[3].text = {}
gr_edit legend.plotregion1.label[3].text.Arrpush Other Race
gr_edit legend.plotregion1.key[1].xsz.editstyle 6 editcopy
gr_edit legend.plotregion1.key[2].xsz.editstyle 6 editcopy
gr_edit legend.Edit , style(col_gap(small)) style(key_gap(minuscule)) style(key_xsize(medium)) keepstyles 
gr_edit legend.draw_view.setstyle, style(no)


***/// Figure 4: Experimtent 2: Specific Fear by Pair Composition of Pictured Officers ///***


regress normsf i.offrace i.offsex i.MANIPULATION_A normpf if raceg ==2 [pw = combweight], robust
estimates store Blacks
regress normsf i.offrace i.offsex i.MANIPULATION_A normpf if raceg < 2 [pw = combweight], robust
estimates store NonBlacks

coefplot Blacks, bylabel(Black Respondents) || NonBlacks, bylabel(Non-Black Respondents) ||, drop (_cons normpf) xline(0) ///
	xtitle(Effect on Fear of Pictured Officers) omitted baselevels ylab(, labs(small)) msize(small) ///
	headings(0.offrace="{bf:Officers Race}"0.offsex="{bf:Officers Sex}" ///
	1.MANIPULATION_A="{bf:Location}" , labsize (small) labgap(0))

gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 7 12 `"Empty Street"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 8 13 `"Busy Street"', tickset(major)
gr_edit plotregion1.xaxis1[1].reset_rule -15 5 5 , tickset(major) ruletype(range) 
gr_edit plotregion1.xaxis1[2].reset_rule -15 5 5 , tickset(major) ruletype(range) 	
gr_edit plotregion1.xaxis1[1].style.editstyle majorstyle(tickstyle(textstyle(size(small)))) editcopy
gr_edit plotregion1.xaxis1[1].style.editstyle majorstyle(use_labels(no)) editcopy
gr_edit plotregion1.xaxis1[1].style.editstyle majorstyle(alternate(no)) editcopy
gr_edit subtitle.DragBy -.2250479492786635 11.58996938785265
gr_edit subtitle.DragBy -.1125239746393083 .4500958985573741
gr_edit b1title.DragBy -.2250479492786909 16.31597632270523
gr_edit b1title.DragBy -.9001917971147737 .1125239746393552
gr_edit b1title.DragBy 0 -5.319762541990731


***/// Figure 5: Experimtent 2: Specific Fear of Pictured Officers, by Officer ///***


regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg ==2 [pw = combweight], robust
estimates store Blacks
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg < 2 [pw = combweight], robust
estimates store NonBlacks

coefplot Blacks, bylabel(Black Respondents) || NonBlacks, bylabel(Non-Black Respondents) ||, drop (_cons normpf) xline(0) ///
	xtitle(Effect on Fear of Pictured Officers) omitted baselevels ylab(, labs(small)) msize(small) ///
	headings(0.po_race1="{bf:Officer 1 Race}" 0.po_sex1="{bf:Officer 1 Sex}" 0.po_race2="{bf:Officer 2 Race}" ///
	0.po_sex2="{bf:Officer 2 Sex}" 1.MANIPULATION_A="{bf:Location}", labsize (small) labgap(0))
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 1 2 `"White"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 1 2 `"White"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 2 3 `"Latino"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 2 3 `"Hispanic/Latino"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 3 4 `"Black"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 4 7 `"Male"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 5 8 `"Female"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 6 11 `"White"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 7 12 `"Hispanic/Latino"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 8 13 `"Black"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 9 16 `"Male"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 10 17 `"Female"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 11 20 `"Empty Street"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 12 21 `"Busy Street"', tickset(major)
gr_edit b1title.DragBy -.1125239746393474 8.889393996508384
gr_edit b1title.DragBy -.67514384783608 2.925623340623017
gr_edit b1title.DragBy 0 -1.012715771754134
gr_edit plotregion1.xaxis1[1].reset_rule -16 16 8 , tickset(major) ruletype(range) 
gr_edit plotregion1.xaxis1[2].reset_rule -16 16 8 , tickset(major) ruletype(range) 	
gr_edit plotregion1.xaxis1[1].style.editstyle majorstyle(tickstyle(textstyle(size(small)))) editcopy
gr_edit plotregion1.xaxis1[1].style.editstyle majorstyle(use_labels(no)) editcopy
gr_edit plotregion1.xaxis1[1].style.editstyle majorstyle(alternate(no)) editcopy
gr_edit b1title.DragBy -.2250479492786958 -.7876678224754241


***/// Figure 6: Experimtent 2: Adjusted Predictions for Specific Fear ///***


regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg ==2 [pw = combweight], robust
margins, at(po_race1 = (0) po_race2 = (0) po_sex1 = (0) po_sex2 = (0)) atmeans vsquish noatlegend post
estimates store BWWMM
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg ==2 [pw = combweight], robust
margins, at(po_race1 = (2) po_race2 = (2) po_sex1 = (0) po_sex2 = (0)) atmeans vsquish noatlegend post
estimates store BBBMM
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg ==2 [pw = combweight], robust
margins, at(po_race1 = (0) po_race2 = (0) po_sex1 = (1) po_sex2 = (1)) atmeans vsquish noatlegend post
estimates store BWWFF
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg ==2 [pw = combweight], robust
margins, at(po_race1 = (2) po_race2 = (2) po_sex1 = (1) po_sex2 = (1)) atmeans vsquish noatlegend post
estimates store BBBFF

regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg <2 [pw = combweight], robust
margins, at(po_race1 = (0) po_race2 = (0) po_sex1 = (0) po_sex2 = (0)) atmeans vsquish noatlegend post
estimates store NWWMM
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg <2 [pw = combweight], robust
margins, at(po_race1 = (2) po_race2 = (2) po_sex1 = (0) po_sex2 = (0)) atmeans vsquish noatlegend post
estimates store NBBMM
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg <2 [pw = combweight], robust
margins, at(po_race1 = (0) po_race2 = (0) po_sex1 = (1) po_sex2 = (1)) atmeans vsquish noatlegend post
estimates store NWWFF
regress normsf i.po_race1 i.po_sex1 i.po_race2 i.po_sex2 i.MANIPULATION_A normpf if raceg <2 [pw = combweight], robust
margins, at(po_race1 = (2) po_race2 = (2) po_sex1 = (1) po_sex2 = (1)) atmeans vsquish noatlegend post
estimates store NBBFF

coefplot NWWMM NWWFF NBBMM NBBFF BWWMM BWWFF BBBMM BBBFF, recast(bar) barwidth(0.1) finten(70) ciopt(recast(rcap)) 
gr_edit yaxis1.major.num_rule_ticks = 0
gr_edit yaxis1.edit_tick 1 1 `"_cons"', custom tickset(major) editstyle(tickstyle(show_labels(no)) tickstyle(show_ticks(no)) )
gr_edit yaxis1.add_ticks .50 `"Officer Attributes"', tickset(major)
gr_edit yaxis1.major.num_rule_ticks = 0
gr_edit yaxis1.edit_tick 2 0.5 `"{bf:Officer Attributes} "', custom tickset(major) editstyle(tickstyle(linestyle(color(none))) )
gr_edit yaxis1.add_ticks .61 `"White Males"', tickset(major)
gr_edit yaxis1.add_ticks .72 `"White Females"', tickset(major)
gr_edit yaxis1.add_ticks .83 `"Black Males"', tickset(major)
gr_edit yaxis1.add_ticks .94 `"Black Females"', tickset(major)
gr_edit yaxis1.add_ticks 1.057 `"White Males"', tickset(major)
gr_edit yaxis1.add_ticks 1.165 `"White Females"', tickset(major)
gr_edit yaxis1.add_ticks 1.275 `"Black Males"', tickset(major)
gr_edit yaxis1.add_ticks 1.386 `"Black Females"', tickset(major)
gr_edit plotregion1.plot4.style.editstyle area(shadestyle(color(navy))) editcopy
gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(navy))) editcopy
gr_edit plotregion1.plot6.style.editstyle area(shadestyle(color(navy))) editcopy
gr_edit plotregion1.plot6.style.editstyle area(linestyle(color(navy))) editcopy
gr_edit plotregion1.plot8.style.editstyle area(shadestyle(color(navy))) editcopy
gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(navy))) editcopy
gr_edit plotregion1.plot2.style.editstyle area(shadestyle(color("%50"))) editcopy
gr_edit plotregion1.plot2.style.editstyle area(linestyle(color("%50"))) editcopy
gr_edit plotregion1.plot4.style.editstyle area(shadestyle(color("%50"))) editcopy
gr_edit plotregion1.plot4.style.editstyle area(linestyle(color("%50"))) editcopy
gr_edit plotregion1.plot6.style.editstyle area(shadestyle(color("%50"))) editcopy
gr_edit plotregion1.plot6.style.editstyle area(linestyle(color("%50"))) editcopy
gr_edit plotregion1.plot8.style.editstyle area(shadestyle(color("%50"))) editcopy
gr_edit plotregion1.plot8.style.editstyle area(linestyle(color("%50"))) editcopy
gr_edit plotregion1.plot3.style.editstyle area(linestyle(color(navy))) editcopy
gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(navy))) editcopy
gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(navy))) editcopy
gr_edit plotregion1.plot10.style.editstyle area(shadestyle(color(maroon))) editcopy
gr_edit plotregion1.plot10.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot12.style.editstyle area(shadestyle(color(maroon))) editcopy
gr_edit plotregion1.plot12.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot14.style.editstyle area(shadestyle(color(maroon))) editcopy
gr_edit plotregion1.plot14.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot16.style.editstyle area(shadestyle(color(maroon))) editcopy
gr_edit plotregion1.plot16.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot10.style.editstyle area(shadestyle(color("%75"))) editcopy
gr_edit plotregion1.plot10.style.editstyle area(linestyle(color("%75"))) editcopy
gr_edit plotregion1.plot10.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit plotregion1.plot12.style.editstyle area(shadestyle(color("%75"))) editcopy
gr_edit plotregion1.plot12.style.editstyle area(linestyle(color("%75"))) editcopy
gr_edit plotregion1.plot12.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit plotregion1.plot14.style.editstyle area(shadestyle(color("%75"))) editcopy
gr_edit plotregion1.plot14.style.editstyle area(linestyle(color("%75"))) editcopy
gr_edit plotregion1.plot14.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit plotregion1.plot16.style.editstyle area(shadestyle(color("%75"))) editcopy
gr_edit plotregion1.plot16.style.editstyle area(linestyle(color("%75"))) editcopy
gr_edit plotregion1.plot16.style.editstyle area(shadestyle(intensity(100))) editcopy
gr_edit plotregion1.plot9.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot11.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot13.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit plotregion1.plot15.style.editstyle area(linestyle(color(maroon))) editcopy
gr_edit xaxis1.reset_rule 30 90 10 , tickset(major) ruletype(range) 
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit title.text = {}
gr_edit title.text.Arrpush Predicted Fear of Pictured Officers
gr_edit title.style.editstyle color(black) editcopy
gr_edit title.style.editstyle size(medium) editcopy
gr_edit legend.plotregion1.label[2].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.key[2].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.key[4].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[4].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.key[6].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[6].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.key[8].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[8].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.key[3].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[3].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.key[7].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[7].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[1].text = {}
gr_edit legend.plotregion1.label[1].text.Arrpush Non-Black Respondents
gr_edit legend.plotregion1.label[5].text = {}
gr_edit legend.plotregion1.label[5].text.Arrpush Black Respondents
gr_edit legend.Edit , style(row_gap(zero)) style(col_gap(zero)) keepstyles 
gr_edit legend.plotregion1.label[3].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[7].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[2].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[4].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[6].draw_view.setstyle, style(no)
gr_edit legend.plotregion1.label[8].draw_view.setstyle, style(no)



*************************//// Experimtent 1: Main Analysis for Conjoint ///*************************



***/// Reshape Data Wide to Long ///***


reshape long officer_race officer_gender officer_age officer_build officer_educ officer_cam officer_complain officer_choice, i(caseid) j(profile)
encode officer_race, gen (orace)
encode officer_gender, gen (ogender)
encode officer_age, gen (oage)
encode officer_build, gen (obuild)
encode officer_educ, gen (oeduc)
encode officer_cam , gen (ocam)
encode officer_complain, gen (ocomplain)


***/// Recode Cojoint Predictors ///***


recode orace (3=0) (1=2) (2=1), gen (oraceR)
label define oraceR 0 "0. White" 1 "1. Hispanic/Latino" 2 "2. Black"
label values oraceR oraceR

recode ogender (2=0) (1=1), gen (ogenderR)
label define ogenderR 0 "0. Male" 1 "1. Female"
label values ogenderR ogenderR

recode obuild (3=0) (2=1) (1=2), gen (obuildR)
label define obuildR 0 "0. Thin" 1 "1. Overweight" 2 "2. Muscular"
label values obuildR obuildR

recode oeduc (3=0), gen (oeducR)
label define oeducR 0 "0. High School" 1 "1. Associate Degree" 2 "2. Bachelor's Degree"
label values oeducR oeducR

recode ocomplain (1=0) (2=1) (3=3) (4=2), gen (ocomplainR)
label define ocomplainR 0 "0. None" 1 "1. Disrespect" 2 "2. Excessive Force" 3 "3. Disrespect and Excessive Force"
label values ocomplainR ocomplainR


***/// Figure 3: Which Officer Most Afraid ///***


regress officer_choice i.oraceR i.ogenderR i.oage i.obuildR i.oeducR i.ocam i.ocomplainR if raceg ==2 [pw = combweight], cluster (caseid)
estimates store black
regress officer_choice i.oraceR i.ogenderR i.oage i.obuildR i.oeducR i.ocam i.ocomplainR if raceg <2 [pw = combweight], cluster (caseid)
estimates store nonblack

coefplot black, bylabel(Black Respondents) || nonblack, bylabel(Non-Black Respondents) ||, drop (_cons) xline(0) ///
	xtitle(Effect on Probability of Fear) omitted baselevels ylab(, labs(small)) msize(small) headings(0.oraceR="{bf:Race}" 0.ogenderR="{bf:Gender}" ///
	1.oage="{bf:Age}" 0.obuildR="{bf:Body Build}" 0.oeducR="{bf:Education}" 1.ocam="{bf:Body Camera}" ///
	0.ocomplainR="{bf:Past Complaints}", labsize (small) labgap(0))

gr_edit plotregion1.subtitle[1].style.editstyle size(medsmall) editcopy
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 1 2 `"White"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 2 3 `"Hispanic/Latino"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 3 4 `"Black"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 4 7 `"Male"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 5 8 `"Female"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 6 11 `"25"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 7 12 `"35"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 8 13 `"45"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 9 14 `"55"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 10 17 `"Thin"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 11 18 `"Overweight"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 12 19 `"Muscular"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 13 22 `"High School"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 14 23 `"Associate Degree"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 15 24 `"Bachelor's Degree"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 16 27 `"No"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 17 28 `"Yes"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 18 31 `"None"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 19 32 `"Disrespect"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 20 33 `"Excessive Force"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 21 34 `"Disrespect and Excessive Force"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 22 1 `"{bf:Officer Race}"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 23 6 `"{bf:Officer Sex}"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 24 10 `"{bf:Officer Age}"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 25 16 `"{bf:Officer Body Type}"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 26 21 `"{bf:Officer Education}"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 27 26 `"{bf:Officer Body Camera}"', tickset(major)
gr_edit plotregion1.yaxis1[1].major.num_rule_ticks = 0
gr_edit plotregion1.yaxis1[1].edit_tick 28 30 `"{bf:Officer Past Complaints}"', tickset(major)
gr_edit style.editstyle boxstyle(shadestyle(color(white))) editcopy
gr_edit style.editstyle boxstyle(linestyle(color(white))) editcopy
gr_edit b1title.DragBy -.1156470117824042 15.26540555527771
gr_edit b1title.DragBy -1.156470117824067 .1156470117823964
gr_edit b1title.DragBy 0 2.363003467426225
gr_edit b1title.DragBy 0 -.6751438478361155


